Pradeep Shenoy

Pradeep Shenoy

Pradeep Shenoy leads the Cognitive modeling & Machine Learning team at Google Research India, which aims to build expressive, robust ML systems, drawing functional and algorithmic inspiration from human cognition. Pradeep also works on modeling human behavior & cognition, with applications in personalization and human-AI interfaces. Recent work has focused on robust learning via instance reweighting, and its application to a range of problem settings in applied ML. Pradeep has a Ph.D. in Computer Science from the University of Washington & post-doctoral research experience at UC San Diego, where he worked in neuroengineering, computational neuroscience & cognitive science. He has previously led machine learning teams at Microsoft, developing and supporting large-scale production models that predict user behavior (clicks, conversions, audience segmentation, etc.) in sponsored search. Pradeep has also worked in various capacities at Microsoft Research, Fraunhofer Institute, and Lucent Bell Laboratories.
Authored Publications
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    Google
Using Early Readouts to Mediate Featural Bias in Distillation
Rishabh Tiwari
Durga Sivasubramanian
Anmol Mekala
Ganesh Ramakrishnan
WACV 2024 (2024)
Overcoming simplicity bias in deep networks using a feature sieve
Rishabh Tiwari
International Conference on Machine Learning (ICML) (2023) (to appear)
Interactive Concept Bottleneck Models
Rishabh Tiwari
Jan Freyberg
Dj Dvijotham
AAAI (2023)
Adaptive mixing of auxiliary losses in supervised learning
Durga Sivasubramanian
Ayush Maheshwari
Prathosh AP
Ganesh Ramakrishnan
AAAI 2023 (2023) (to appear)
Edges to Shapes to Concepts: Adversarial Augmentation for Robust Vision
Aditay Tripathi
Rishubh Singh
Anirban Chakraborty
Computer Vision and Pattern Recognition (CVPR) 2023 (2023) (to appear)